{"id":"W2144305718","doi":"","title":"Do administrative databases accurately measure waiting times for medical care? Evidence from general surgery.","year":2007,"lang":"en","type":"article","venue":"PubMed","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Medical record; Gold standard (test); Waiting list; Medical emergency; Database; Measure (data warehouse); MEDLINE; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03919398,0.0007175349,0.001232543,0.004130426,0.0004799517,0.001912191,0.002410495,0.001059563,0.002135084],"category_scores_gemma":[0.2253013,0.0007073022,0.002265291,0.008797842,0.0010994,0.001775061,0.001483605,0.001095569,0.0003493527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001914029,"about_ca_system_score_gemma":0.003440725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0550086,"about_ca_topic_score_gemma":0.04508379,"domain_scores_codex":[0.9587414,0.02797809,0.00456027,0.001915346,0.005992799,0.0008118899],"domain_scores_gemma":[0.6223261,0.2754724,0.06141845,0.01617268,0.02211189,0.002498424],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004024283,0.0001498657,0.8917449,0.007067073,0.009311905,0.0000957239,0.0006930422,0.0005594242,0.00006510482,0.0009602366,0.002732211,0.08259625],"study_design_scores_gemma":[0.001052551,0.001139483,0.9578876,0.00886557,0.01317616,0.0003364575,0.001038905,0.001758547,0.0002266077,0.001084252,0.01334884,0.00008502955],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5961514,0.3658218,0.004503659,0.008316262,0.0008861555,0.0004538683,0.01367117,0.00004847327,0.01014726],"genre_scores_gemma":[0.9527689,0.03781028,0.003075483,0.001383071,0.0003361686,0.0001333578,0.00425606,0.0000181981,0.0002184873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.960806,"threshold_uncertainty_score":0.2072801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4334853964301215,"score_gpt":0.4962264501091467,"score_spread":0.06274105367902522,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}